code: def set_pytorch_thread(optimized_model_thread_num, thread_num):
      # optimized_model_thread_num is None means no limit is set, just keep current thread num
      if (
          optimized_model_thread_num is not None
          and optimized_model_thread_num != thread_num
      ):
          thread_num = optimized_model_thread_num
          torch.set_num_threads(thread_num)
      return thread_num
  
imports: import torch
  import torch.nn
  import warnings
  import random
  import numpy
  from torch.utils.data import TensorDataset, DataLoader
  import numpy
  import multiprocessing
  import warnings
  import math
label_desc: Use image node_id 16 for calling a global function with example usage: set_pytorch_thread(optimized_model_thread_num, thread_num) and returns: thread_num